Point72 - Senior Data Engineer, Mi-Platform
Requirements
• 5+ years of experience in Data Engineering, Software Engineering or related field • 2+ years of strong experience in Python development • Experience with system design and leading multi-person development efforts • Experience with distributed data processing frameworks like Spark • Experience with building scalable APIs, and software applications w/ focus on backend infrastructure • Experience with cloud platforms and services for data storage and compute (for example AWS, Google Cloud Platform, or Azure) • Experience with orchestration technologies like Airflow • Knowledge of/experience with langraph/langchain or similar frameworks, embedding models, vector, graph databases is a plus • A strong drive to staying current with AI advancements and translating emerging techniques into practical, real-world applications. • Commitment to the highest ethical standards. • We take care of our people • We invest in our people, their careers, their health, and their well-being. When you work here, we provide: • Private Medical and Dental Insurances • Generous parental and family leave policies • Volunteer opportunities • Support for employee-led affinity groups representing women, people of colour and the LGBQT+ community • Mental and physical wellness programmes • Tuition assistance • Non-contributory pension and more • Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry's brightest talent by cultivating an investor-led culture and committing to our people's long-term growth. For more information, visit https://point72.com/
Responsibilities
• Work closely with investment professionals, researchers, and data scientists to design, build, and launch robust end-to-end business solutions including data pipelines, products and tools. • Design and develop big data processing pipelines including but not limited to ingestion, transformation, trends creation to deliver AI-ready data assets & products. • Develop reusable software components, libraries, and APIs that enable rapid experimentation and production deployment • Implement data quality, lineage, and governance controls to ensure datasets are reliable, auditable, and compliant with compliance policies • Build scalable AI-native cloud-based infrastructure using distributed systems techniques, to deliver efficient data-driven business solutions • Optimize performance, cost, and reliability of software systems through benchmarking and iterative improvements
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